Longitudinal data are available in many disciplines, and quite often the mechanism generating the data are changing over time. These changes must be accounted for when modelling the data and subsequently drawing conclusions from the data. The three statistical models described in this article (GARCH, HMM, ARHMM) are appropriate modelling data with such changes. These three models are generalizations of a random walk. In a random walk the random changes over time have a constant distribution. The three models illustrated account for changes in the distribution of the random displacements over time. Our purpose in the article is to illustrate these three models and their intricacies using Excel. We would also contend and encourage the application of these three models to the analysis of other continuous data in fields utilizing social and medical data.